Extracting token-level signals of syntactic processing from fMRI - with an application to PoS inductionExtracting token-level signals of syntactic processing from fMRI - with an application to PoS inductionBingel, Joachim and Barrett, Maria and Søgaard, Anders2016

Paper summarymarekThey incorporate fMRI features into POS tagging, under the assumption that reading semantically/functionally different words will activate the brain in different ways. For this they use a dataset of fMRI recordings, where the subjects were reading a chapter of Harry Potter. The main issue is that fMRI has very low temporal resolution – there is only one fMRI reading per 4 tokens, and in general it takes around 4-14 seconds for something to show up in fMRI. Nevertheless, they construct token-level vectors by using a Gaussian weighted average, integrate them into an unsupervised POS tagger, and show that it is able to improve performance.
https://i.imgur.com/TU60N6w.png

They incorporate fMRI features into POS tagging, under the assumption that reading semantically/functionally different words will activate the brain in different ways. For this they use a dataset of fMRI recordings, where the subjects were reading a chapter of Harry Potter. The main issue is that fMRI has very low temporal resolution – there is only one fMRI reading per 4 tokens, and in general it takes around 4-14 seconds for something to show up in fMRI. Nevertheless, they construct token-level vectors by using a Gaussian weighted average, integrate them into an unsupervised POS tagger, and show that it is able to improve performance.
https://i.imgur.com/TU60N6w.png